Techniques for training robots for dexterous manipulation tasks

A method for training a robotic system comprising:

• manually manipulating, using a passive exoskeleton, one or more parameters of an end effector to manipulate an object;
• transmitting, using one or more linkages of the passive exoskeleton, forces applied to the end effector to a portion of a user's body due to interactions of the end effector with a surrounding environment;
• and
• sensing, using one or more sensors, one or more parameters of the end effector while facilitating manipulation of the object to generate a training dataset for operation of the robotic system.

At least one computer-readable storage medium storing processor executable instructions that, when executed by at least one hardware processor, cause the at least one hardware processor to:

• receive, using at least one communication interface, sensor data from one or more sensors configured to sense one or more parameters of an end effector when the end effector is manually manipulated by a passive exoskeleton to manipulate an object;
• generate, using the sensor data, a training dataset for operation of a robotic system comprising the end effector;
• and
• cause a change in the one or more parameters of the end effector to manipulate the object in accordance with the training dataset.